Principal Product Manager, Data Platform

Expedia Expedia · Hospitality · London, United Kingdom

Product Manager to own the vision and roadmap for an AI-enhanced data catalog, focusing on data discoverability, metadata capture, governance, and self-service UIs/APIs. The role involves embedding AI-driven features like semantic search and natural language query to improve data usability and accelerate initiatives.

What you'd actually do

  1. Own and drive the vision, strategy, and multi-year roadmap for an AI-enhanced data catalog that makes trusted data assets searchable, understandable, and reusable across the organization.
  2. Define and deliver scalable data platform capabilities spanning metadata capture (schemas, lineage, data contracts), governance, discovery, and access via self-service UIs and APIs.
  3. Embed AI-driven discovery features such as semantic search, natural language query, and recommendations to improve data discoverability and reduce time to insight.
  4. Translate complex platform and business needs into a clear, outcome-driven roadmap, prioritizing based on impact, feasibility, and measurable results.
  5. Define and track adoption and impact metrics (e.g., catalog usage, certified dataset ratio, time-to-find reductions, user satisfaction).

Skills

Required

  • 10+ years of product management or related technology experience, including ownership of complex platform or data products.
  • Experience leading data-centric products or platforms (e.g., data catalogs, metadata systems, data quality frameworks, data contracts, analytics enablement platforms).
  • Deep background in data analysis, analytics, or data engineering, with strong understanding of data ecosystems and workflows.
  • Proven track record of defining and executing product strategy and roadmaps for complex, cross-functional data platforms, with measurable business impact.
  • Strong technical fluency in APIs, data modeling, and distributed systems, including experience working on always-on data platforms and data flow architectures.
  • Demonstrated ability to collaborate closely with engineering and data teams to deliver technically sophisticated platform capabilities (e.g., metadata capture, lineage, discoverability tooling).
  • Experience defining and driving adoption and success metrics (e.g., usage, data discoverability, time-to-insight, user satisfaction).
  • Proven ability to influence senior stakeholders and cross-functional teams on prioritization, governance, and trade-offs, and to clearly articulate the business value of data discoverability.

Nice to have

  • Experience leading enterprise-scale data platforms or data catalogs with broad adoption.
  • Track record in platform governance, data quality, and self-service enablement.
  • Expertise in metadata management and data discoverability, including lineage, certification, and data contracts.
  • Experience building or integrating AI/ML-powered platform capabilities (e.g., semantic search, recommendations, NLP interfaces).
  • Strong ability to influence architecture and operating models without direct authority.
  • Experience using data to measure platform adoption, product health, and operational performance

What the JD emphasized

  • AI-enhanced data catalog
  • data discoverability
  • semantic search
  • natural language query
  • recommendations
  • metadata capture
  • governance
  • self-service UIs and APIs
  • data trust and certification framework
  • observability
  • SLAs
  • platform quality, scalability, and governance

Other signals

  • AI-enhanced data catalog
  • semantic search
  • natural language query
  • recommendations
  • data discoverability